This paper examines the time-varying conditional correlations between Bitcoin future market and five FOREX future markets. A sixvariate dynamic conditional correlation (DCC) GARCH model is applied in order to capture potential contagion effects between the markets for the period 2017-2019....

We propose a model that extends the RT-GARCH model by allowing conditional heteroskedasticity in the volatility process. We show we are able to filter and forecast both volatility and volatility of volatility simultaneously in this simple setting. The volatility forecast function follows a...

The present study attempts to examine the dual impact of changes in interest rate and interest rate volatility on the mean and variance of portfolio stock returns. The study period is from 1st April 1996 to 30th August 2014 covering a total period of approximately 18 years. Sample used in the...

We propose a novel empirical strategy that enables the researcher to select buckets of volatility forecasting models with similar accuracy. Using our Multiple Hypothesis Testing framework with False Discovery Rate (FDR) approach, we are able to identify buckets of more accurate models relative...

We propose a multiplicative factor multi frequency component GARCH model which exploits the empirical fact that the daily standardized forecast errors of one-component GARCH models behave counter-cyclical when averaged at a lower frequency. For the new model, we derive the unconditional variance...

Short-term electricity price forecasting has received considerable attention in recent years. Despite this increased interest, the literature lacks a concrete consensus on the most suitable forecasting approach. We conduct an extensive empirical analysis to evaluate the short-term price...

Starting from the Cholesky-GARCH model, recently proposed by Darolles, Francq, and Laurent (2018), the paper introduces the Block-Cholesky GARCH (BC-GARCH). This new model adapts in a natural way to the asset pricing framework. After deriving conditions for stationarity, uniform invertibility...

The role of public sentiment in stock market volatility has recently become increasingly relevant. Twitter, in theory, offers an inexpensive way to measure real-time public sentiment. We take advantage of a natural experiment to assess the potential improvement that social media adds to forecast...

Several procedures to estimate daily risk measures in cryptocurrency markets have been recently proposed in the literature. Among them, procedures taking into account the presence of extreme observations, as well as procedures that include more than a single regime, have performed substantially...